Staff AI & Data Engineer, Databricks — Remote

Eliassen Group; United States; Remote; USD 110,000 - 124,000; Full time

Job summary

Eliassen Group is seeking a highly experienced Staff AI & Data Engineer to design and build enterprise-grade data and AI solutions on Databricks. This hands-on role strengthens the Databricks platform, onboarding new data sources, and creating trusted Gold-layer data products.

You will develop semantic layers, AI agents, and governance, working across pipelines, data quality, and cross-domain analytics, with a focus on experimental AI readiness and scalable architectures.

Qualifications

• Advanced hands-on experience with Databricks, Apache Spark, Delta Lake, and SQL.
• Hands-on experience with AWS services related to data analytics and AI, including EMR and Bedrock.
• Strong Python and SQL development skills.
• Experience building scalable batch and/or streaming data pipelines.
• Deep understanding of Bronze/Silver/Gold medallion architectures.
• Experience with Databricks Lakeflow or comparable orchestration technologies.
• Experience implementing enterprise data quality, lineage, observability, and monitoring.
• Experience with Unity Catalog and governed enterprise data environments.
• Strong understanding of dimensional modeling, data products, semantic models, and cross-domain integration.
• Experience with Git-based development, CI/CD, automated testing, and production deployment.
• Ability to troubleshoot complex distributed data and pipeline issues.
• Experience building AI and GenAI solutions against enterprise data.
• Understanding of semantic layers and natural-language-to-data architectures.
• Experience with Databricks Genie or comparable natural-language analytics technology.
• Experience building tools, functions, APIs, or services consumed by AI agents.
• Understanding of MCP, agent tool calling, tracing, evaluation, and AI governance.
• Experience developing production AI solutions with security, observability, and governance controls.

Responsibilities

• Design and build production-grade data pipelines on Databricks.
• Ingest data from enterprise applications, databases, APIs, SaaS platforms, files, and other source systems.
• Build and maintain Bronze, Silver, and Gold medallion architectures.
• Implement incremental processing and change data capture patterns where appropriate.
• Standardize types, codes, units, keys, and business definitions across source systems.
• Implement deduplication, historical tracking, schema evolution, and data lineage.
• Optimize pipelines for reliability, performance, scalability, and cost.
• Build a configuration-driven source onboarding framework and Lakeflow pipeline templates.
• Automate source registration, deployment, monitoring, lineage, and operational controls.
• Implement data quality expectations, anomaly detection, monitoring, and quarantine processes.
• Implement job and pipeline monitoring, alerting, audit logging, and operational dashboards.
• Support automated deployment and promotion using Databricks Asset Bundles and CI/CD.
• Develop conformed dimensions and shared-key strategies across domains.
• Build integrated Gold-layer products and reusable data contracts.
• Build AI-ready Gold data products with ownership, lineage, definitions, and quality information.
• Develop semantic context, business glossary, ontology, and certified KPIs in Unity Catalog.
• Build governed Unity Catalog functions and agent-ready tools and endpoints.
• Implement tracing, evaluation, testing, monitoring, and governance for AI and agent workflows.
• Support development of AI agents that use trusted enterprise data.

Skills

Databricks

Apache Spark

Delta Lake

SQL

Python

AWS

CI/CD

Git

Data pipelines

GenAI

Tools

Databricks Lakeflow

Unity Catalog

MLflow

Bedrock

EMR

Databricks Genie

Job description

Eliassen Group is seeking a highly experienced Staff AI & Data Engineer to design and build enterprise-grade data and AI solutions on Databricks. This hands-on role strengthens the Databricks platform, onboarding new data sources, and creating trusted Gold-layer data products.

You will develop semantic layers, AI agents, and governance, working across pipelines, data quality, and cross-domain analytics, with a focus on experimental AI readiness and scalable architectures.